X-Git-Url: https://www.fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=dagnn.git;a=blobdiff_plain;f=README.md;h=fa77a7e785ccdb23880cacdea55e5d609f294399;hp=869a1d97c09df81fd886168e78159bc56b7f8bdf;hb=HEAD;hpb=91d22819226af01ec2eee6aed49007e058dc6e50

diff --git a/README.md b/README.md
index 869a1d9..fa77a7e 100644
--- a/README.md
+++ b/README.md
@@ -1,9 +1,8 @@
-
 # Introduction #
 
-This package implements a new module nn.DAG for the torch framework,
-which inherits from nn.Container and allows to combine modules in an
-arbitrary graph without cycle.
+This package implements a new module nn.DAG for the [torch framework](https://torch.ch),
+which inherits from [nn.Container](https://github.com/torch/nn/blob/master/Container.lua) and allows to combine modules in an
+arbitrary [Directed Acyclic Graph (DAG).](https://en.wikipedia.org/wiki/Directed_acyclic_graph)
 
 ## Example ##
 
@@ -67,7 +66,7 @@ table of inputs reflecting the structure of the nested table of
 modules given as argument to DAG:setInput (respectively DAG:setOutput)
 
 So for instance, in the example above, the model expects a tensor as
-input, since it is the input to the module a, and its output will is a
+input, since it is the input to the module a, and its output is a
 table composed of two tensors, corresponding to the outputs of d and e
 respectively.
 
@@ -77,20 +76,27 @@ respectively.
 
 Create a new empty DAG, which inherits from nn.Container.
 
-### nn.DAG:connect([module1 [, module2 [, ...]]]) ###
+### nn.DAG:connect(module1, module2 [, module3, [...]]) ###
 
 Add new nodes corresponding to the modules passed as arguments if they
 have not been already added in a previous call. Add edges between
-every two nodes associated to two successive modules in the arguments.
+every two nodes associated to two successive modules in the
+arguments.
 
 Calling this function with n > 2 arguments is strictly equivalent to
 calling it n-1 times on the pairs of successive arguments.
 
+Accepting more than two arguments allows in particular to add
+anonymous modules, which are not associated to variables. In principle
+the only ones that have to be non-anonymous are those that have more
+than one successor/predecessor and/or are inputs/outputs.
+
 ### nn.DAG:setInput(i) ###
 
-Defines the content and structure of the input. The argument should be
+Define the content and structure of the input. The argument should be
 either a module, or a (nested) table of modules. The input to the DAG
-should be a (nested) table of inputs, with the corresponding structure.
+should be a (nested) table of inputs, with the corresponding
+structure.
 
 ### nn.DAG:setOutput(o) ###
 
@@ -98,17 +104,18 @@ Similar to DAG:setInput().
 
 ### nn.DAG:print() ###
 
-Prints the list of nodes.
+Print the list of nodes.
 
 ### nn.DAG:saveDot(filename) ###
 
 Save a dot file to be used by the Graphviz set of tools for graph
 visualization. This dot file can than be used for instance to produce
-a pdf file with
+a pdf file such as [this one](https://fleuret.org/git-extract/dagnn/graph.pdf) with
 
 ```
 dot graph.dot -T pdf -o graph.pdf
 ```
 
--- 
-*Francois Fleuret, Jan 13th, 2017*
+### nn.DAG:setLabel(module, name) ###
+
+Add a label to the given module, that will be used for DAG:print() and DAG:saveDot()